AI Strategy Assistant
AI Strategy Assistant —
Turn Your Instructions into Automated Trades
For traders who already have a strategy in mind: the AI Strategy Assistant turns your investment ideas into reality so you can start automated trading quickly.
How It Works
What Is the MASQuant AI Strategy Assistant?
Inside the app, the AI Strategy Assistant turns your own trading idea into a strategy in six steps:
- Build your trading logic — start from an idea such as a moving-average crossover, RSI overbought/oversold, Bollinger Band breakout or MACD trend strategy, or describe your own trading rules directly.
- Choose technical indicators — combine indicators such as moving averages, RSI, MACD, Bollinger Bands, ATR and Stochastic however you like.
- Set entry and exit conditions — for example, enter when RSI is below 30 and price breaks above the moving average; exit when RSI is above 70 or the stop-loss is triggered.
- AI analysis and parameter optimization — the AI analyses instrument characteristics, volatility structure, market behaviour and historical data to find the parameter combinations that fit best.
- Backtest the strategy — review the return, win rate, maximum drawdown, Sharpe ratio and equity curve.
- Deploy to MT5 — the system generates the executable file and packages the strategy for MT5, so you don’t need to write any MQL5 code.
Core Features
MASQuant AI Strategy Assistant
Describe your trading logic in natural language, for example: “Enter when RSI is below 30 and exit when price breaks above MA20.” The AI Strategy Assistant interprets it in real time and generates the strategy automatically.
Built-in conditions for common technical indicators let you quickly set up a strategy’s entry and exit logic, without the hassle of writing complex formulas.
Based on the strategy logic you enter, the AI Strategy Assistant flags any missing key conditions, such as stop-loss or timeframe, and produces a complete logic summary to help you confirm step by step that the strategy works as intended.
Validate a new strategy’s profit and loss potential and risks with historical data, helping you evaluate its win rate, expected value and maximum drawdown before committing real money, instead of relying on intuition or luck and taking unnecessary losses. Backtests support dynamic charts to help you check strategy stability and see where to optimize.
Intuitive charts show the equity curve, maximum profit and maximum loss, helping you understand the risks in different market scenarios before you place an order.
Set Up Strategy Ideas in Plain Language
Assisted Technical Indicator Selection
AI-Enhanced Strategy Logic
Historical Backtest Validation
Risk Visualization
MASQuant AI Strategy Assistant
Start Trading in Three Steps
1. Sign up for a MASQuant account and choose a plan
2. Use the AI Strategy Assistant to build a personalized strategy and download the trading execution file
3. Connect to your broker’s MT5 account and start automated trading
1. Sign up for a MASQuant account and choose a plan
2. Use the AI Strategy Assistant to build a personalized strategy and download the trading execution file
3. Connect to your broker’s MT5 account and start automated trading
Validate every trading strategy under conditions closer to the real market
MASQuant Backtest Engine
Closer to the real market — validate every trading strategy
MASQuant Backtest Engine
MASQuant has a built-in professional backtesting engine that integrates historical data, real-time market data, and demo trading, so you can fully validate a strategy under near-real market conditions before you deploy it.
MASQuant Backtest Engine
Core Features
Data Sources and Security Management
Built on compliance, information security, and transparency, MASQuant is an international quant trading platform that investors, strategy developers, trading teams, and B2B partners can use with peace of mind.
Supports Major Brokers
European and Global Exchange Data Support
MASQuant currently integrates financial market data through the MT5 environment.
Supports major brokers worldwide
Supported Brokers
MASQuant Platform — Supports 90% of Brokers Worldwide
MASQuant Platform —
Supports 90% of Brokers Worldwide
Supports 90% of brokers worldwide — and many more than we can list here
Supported Instruments
The MASQuant Platform Supports Major CFD Instruments
EURUSD
GBPUSD
AUDUSD
USDCAD
USDCHF
NZDUSD
EURGBP
XAUUSD
More instruments are being added…
Supported Markets
Market Types Supported by the MASQuant Platform
Enterprise-Grade Security
We use high-standard, enterprise-grade information security: we never trade on your behalf, never transmit sensitive data, and never access your account. Every trade and action is completed under your control.
System Requirements
Currently Windows only: MASQuant’s trading features run only on Windows computers. These include downloading strategy execution files, connecting to MT5, setting up automated trading, and executing strategies.
Use a Windows PC for the Following Features
Currently Not Supported
MASQuant Will Keep Evaluating Support for More Platforms
To use strategy execution, MT5 connection, and automated trading, you'll need a Windows computer for installation, setup, and operation. The MASQuant team will keep evaluating support for more platforms and will announce separately if macOS or other systems are supported in the future.
FAQ
Frequently Asked Questions
AI Strategy Assistant FAQ
Who is the AI Strategy Assistant for?
The AI Strategy Assistant is built for traders who already have a trading idea, entry/exit conditions, or a technical-indicator concept in mind, but don't want to write the code themselves.
Just describe your strategy logic in plain language, and the system will help organize, refine, and turn it into backtestable strategy content.
Just describe your strategy logic in plain language, and the system will help organize, refine, and turn it into backtestable strategy content.
Can I describe my trading logic in plain language?
Yes. You can enter your strategy idea in plain language, such as "enter when RSI is below 30, exit when price breaks above MA20."
The AI Strategy Assistant will parse the meaning and organize it into strategy logic you can review and backtest.
The AI Strategy Assistant will parse the meaning and organize it into strategy logic you can review and backtest.
Will the AI Strategy Assistant check whether my strategy logic is complete?
Based on what you enter, the AI Strategy Assistant flags key conditions you may have missed — such as entry, exit, stop-loss, take-profit, or timeframe — and helps produce a logic summary.
You'll still need to confirm for yourself that the finished strategy matches what you intended.
You'll still need to confirm for yourself that the finished strategy matches what you intended.
Will the AI Strategy Assistant add risk controls automatically?
The AI Strategy Assistant can help remind you of stop-loss, take-profit, timeframe, and other risk-control conditions to make your strategy logic more complete.
Which risk-control settings to actually use is still something you need to confirm based on your own capital size, risk tolerance, and trading environment.
Which risk-control settings to actually use is still something you need to confirm based on your own capital size, risk tolerance, and trading environment.
Can AI-generated strategies place orders directly?
Once an AI-generated strategy has been confirmed, backtested, and deployed, it can be used for demo or live trading in the ways the platform supports.
Before actual use, please review the strategy content, backtest results, risk performance, and trading environment, and decide for yourself whether to adopt it.
Before actual use, please review the strategy content, backtest results, risk performance, and trading environment, and decide for yourself whether to adopt it.
Can I modify an AI-generated strategy?
Currently, if you need to adjust the conditions after a strategy has been generated, we recommend re-entering the updated description and regenerating it.
Before going live, please rely on the editing and saving features shown in the current product interface.
Before going live, please rely on the editing and saving features shown in the current product interface.
What risk information can I see after a backtest?
After backtesting, you can review win rate, returns, maximum drawdown, trade history, and other performance metrics; if the page offers risk visualization, charts can also show the equity curve, maximum gain, and maximum loss.
For the exact fields displayed, please refer to your product version.
For the exact fields displayed, please refer to your product version.
Do I need to know how to code to use the AI Strategy Assistant?
No coding required. The AI Strategy Assistant works primarily through natural language and a web interface, so users without a programming background can build strategies, run backtests, and view results.
If you need more advanced development integration, check out our API & Developer Tools separately.
If you need more advanced development integration, check out our API & Developer Tools separately.
Using the AI Strategy Assistant for the first time — where should I start?
We recommend starting with a simple, clearly describable strategy idea — for example, entry conditions, exit conditions, and risk-control conditions.
The workflow is: enter your strategy idea → review the logic the AI has organized → run a backtest → save the strategy → deploy to a demo or live trading environment as needed.
The workflow is: enter your strategy idea → review the logic the AI has organized → run a backtest → save the strategy → deploy to a demo or live trading environment as needed.
Does content generated by the AI Strategy Assistant count as investment advice?
No. The AI Strategy Assistant provides strategy-building and analysis assistance — it is not investment advice, advisory services, discretionary management, or a profit guarantee.
Whether to adopt a strategy, how to set parameters, and whether to trade with real funds remain the user's own decisions, and the user bears the associated trading risk.
Whether to adopt a strategy, how to set parameters, and whether to trade with real funds remain the user's own decisions, and the user bears the associated trading risk.
About the Backtest Engine
What is the MASQuant Backtest Engine?
The MASQuant Backtest Engine validates strategy performance under near-real market conditions before deployment, using historical data, live-market logic, and simulated trading flows.
It's not just a historical performance readout — it gives you a consistent workflow to manage strategies all the way from generation and backtesting through demo trading, deployment, and performance tracking.
It's not just a historical performance readout — it gives you a consistent workflow to manage strategies all the way from generation and backtesting through demo trading, deployment, and performance tracking.
How is MASQuant backtesting different from just looking at past performance?
Standard historical performance is mostly a backward-looking snapshot; the MASQuant Backtest Engine instead brings data integration, format conversion, technical-indicator calculation, the trading model, simulated order execution, and simulated fills together in a single framework.
This lets a strategy be validated, before deployment, in a way that more closely mirrors the real trading process.
This lets a strategy be validated, before deployment, in a way that more closely mirrors the real trading process.
Why should backtesting and live trading use a unified trading architecture?
When backtesting and live trading use different data-processing methods or different execution pipelines, a strategy can show a performance gap once it goes live.
MASQuant routes both historical data and live market data through the same data-integration pipeline before format conversion and indicator calculation, narrowing the technical gap between backtest and live trading.
MASQuant routes both historical data and live market data through the same data-integration pipeline before format conversion and indicator calculation, narrowing the technical gap between backtest and live trading.
Will the backtest engine simulate trading behaviour?
MASQuant's backtest architecture doesn't just simulate price — it also incorporates simulated order execution and fill flows, helping strategy tests more closely mirror real trading execution.
For the exact fill logic, latency, slippage, and market-friction factors supported, please refer to the product version and official technical documentation.
For the exact fill logic, latency, slippage, and market-friction factors supported, please refer to the product version and official technical documentation.
What performance metrics can I see in a backtest?
Backtest performance data currently available includes number of trades, profit/loss ratio, win rate, maximum drawdown, total return, annualized cumulative return, and Sharpe ratio.
For the exact fields displayed, please refer to the current version's page.
For the exact fields displayed, please refer to the current version's page.
What does the backtest report contain?
A backtest report typically includes backtest data, performance metrics, risk metrics, charts, trade history, and a strategy summary.
This information helps you judge whether a strategy has long-term viability, rather than looking only at a single win or loss.
This information helps you judge whether a strategy has long-term viability, rather than looking only at a single win or loss.
How much historical data can I backtest?
Backtesting currently supports up to five years of historical data.
The available historical data range depends on the current product version, instrument support, and data source. For the exact backtestable period, please refer to what's shown in the product.
The available historical data range depends on the current product version, instrument support, and data source. For the exact backtestable period, please refer to what's shown in the product.
Can I backtest and optimize a strategy repeatedly?
Yes. Once a strategy is built, you can backtest it with historical data, then move into demo trading for validation, and only then evaluate whether to deploy it to a live trading environment.
This creates an iterative strategy-development workflow, letting you repeatedly test, adjust, and compare different strategy versions.
This creates an iterative strategy-development workflow, letting you repeatedly test, adjust, and compare different strategy versions.
Do I need to rewrite my trading code to go from backtesting to live deployment?
MASQuant builds backtesting, demo trading, and live trading on a single unified framework, specifically to reduce rewrite costs and process gaps as a strategy moves from testing to deployment.
The exact deployment method still depends on the product version, broker environment, and MT5 configuration.
The exact deployment method still depends on the product version, broker environment, and MT5 configuration.
How can I tell if a strategy is worth deploying?
At minimum, we recommend weighing all of the following: whether the backtest results are stable, whether the risk falls within an acceptable range, whether the instrument and market conditions match your expectations, whether your capital and risk tolerance are a good fit, and whether you're satisfied with the demo account test results.
If any of these remain unclear, we recommend holding off on live trading.
If any of these remain unclear, we recommend holding off on live trading.
Do backtest results mean I'll definitely make money in the future?
No, it does not. Historical performance, backtest data, and illustrative results are provided only to help you understand a strategy's logic and risk characteristics — they should not be taken as a guarantee of future performance.
Real markets remain subject to volatility, liquidity, slippage, broker execution conditions, and other factors beyond anyone's control.
Real markets remain subject to volatility, liquidity, slippage, broker execution conditions, and other factors beyond anyone's control.
What is the difference between backtesting and demo trading?
Backtesting uses historical data to examine how a strategy would have performed under specific past conditions; demo trading, by contrast, lets you get familiar with strategy execution and trading operations in an environment close to live markets.
The recommended order is: backtest first, then demo trade, and only then evaluate whether to move into live trading.
The recommended order is: backtest first, then demo trade, and only then evaluate whether to move into live trading.
What should I do if my backtest doesn't produce results?
Please first check that your strategy conditions are complete, that the instrument and data range are supported, and that your parameter settings are reasonable.
If the product interface offers a clear or reset function, you can also reset your strategy conditions and try again. Contact support if needed.
If the product interface offers a clear or reset function, you can also reset your strategy conditions and try again. Contact support if needed.